Grosinger, Jasmin

Örebro University, School of Science and Technology.

2019 (English)Doctoral thesis, monograph (Other academic)

Abstract [en]

The question addressed in this thesis is: Can we make robots proactive? Proactivity is understood as self-initiated, anticipatory action. This entails the ability to generate own goals and pursue them. Our work is based on the assumption that proactivity makes robots more acceptable in human-inhabited environments. Proactive behavior is opposed to reactive behavior which is merely responding to external events and explicit requests (by the user). We approach the question of how to make robots proactive by first identifying the necessary cognitive capabilities, how they relate and interact. We find that to enable proactive behavior one needs to bridge the gap between context, planning, acting and goal reasoning. We then propose a model of opportunity which formalizes and relates these cognitive capabilities in order to create proactivity. In order to make the model of opportunity computational we introduce a framework called equilibrium maintenance. We show formally and empirically that the framework can make robots act in a proactive way. We can make guarantees about the behavior of a robot acting based on equilibrium maintenance: we prove that given certain assumptions a system employing our framework is kept within desirable states. Equilibrium maintenance is instantiated in different scenarios, both theoretically and in practice by deploying it in a number of systems including both robots and humans. More specifically, we conduct experimental runs in simulation in the domain of robotic disaster management and we implement the framework on a real robot in a domestic environment. The latter is done by integration in different levels, from conceptual examples to closing the loop with a full robotic system. Empirical results confirm that equilibrium maintenance creates proactive behavior and leads to preferable outcomes.

Saffiotti, Alessandro

Abstract [en]

Robots need to exhibit proactive behavior if they are to be accepted in human-centered environments. A proactive robot must reason about the actions it can perform, the state of the environment, the state and the intentions of its users, and what the users deem desirable. This paper proposes a computational framework for proactive robot behavior that formalizes the above ingredients. The framework is grounded on the notion of Equilibrium Maintenance: current and future states are continuously evaluated to identify opportunities for acting that steer the system into more desirable states. We show that this process leads a robot to proactively generate its own goals and enact them, and that the obtained behavior depends on a model of user intentions, preferences, and the temporal horizon used in prediction. A number of examples show that our framework accounts for even slight variations in user preference models and perceived user intentions. We also show how the level of informedness of the system is easily customizable.

Abstract [en]

Proactive cognitive agents need to be capable ofboth generating their own goals and enacting them. In thispaper, we cast this problem as that ofmaintaining equilibrium,that is, seeking opportunities to act that keep the system indesirable states while avoiding undesirable ones. We characterizedesirability of states as graded preferences, using mechanismsfrom the field of fuzzy logic. As a result, opportunities for anagent to act can also be graded, and their relative preferencecan be used to infer when and how to act. This paper providesa formal description of our computational framework, andillustrates how the use of degrees of desirability leads to well-informed choices of action.

Abstract [en]

Robots for the elderly are a particular category of home assistive robots, aiming at assisting the elderly inthe execution of daily life tasks to extend their independent life. To this aim, such robots should be able to determine the level of independence of the user and track its evolution over time, to adapt the assistance to the person capabilities and needs. Human Activity Recognition systems employ various sensing strategies, relying on environmental or wearable sensors,to recognize various daily life activities which provide insights on the health status of a person. The main contribution of the article is the design of an heterogeneous information management framework, allowing for the description of a wide variety of human activities in terms of multi-modal environmental and wearable sensing data and providing accurate knowledge about the user activity to any assistive robot.

Dario, Paolo

Abstract [en]

Robot ecologies are a growing paradigm in which oneor several robotic systems are integrated into a smartenvironment. Robotic ecologies hold great promises forelderly assistance. Planning the activities of these systems,however, is not trivial, and requires considerationof issues like temporal and information dependenciesamong different parts of the ecology, exogenous actions,and multiple, dynamic goals. We describe a plannerable to cope with the above challenges. We showin particular how this planner has been incorporatedin closed-loop into a full robotic system that performsdaily tasks in support of elderly people. The full robotecology is deployed in a test apartment inside a real residentialbuilding, and it is currently undergoing an extensiveuser evaluation.

Saffiotti, Alessandro

Abstract [en]

Under what conditions should a cognitive robot act? How do we define “opportunities” for robot action? How can we characterize their properties? This paper offers an apparatus to frame thediscussion. Starting from a simple introductory example, we specifyan initial version of a formal framework of opportunity which relates current and future states and beneficial courses of action in a certain time horizon. An opportunity reasoning algorithm is presented,which opens up various new questions about the different types of opportunity and how to interleave opportunity reasoning and action execution. An implementation of this algorithm is tested in a simple experiment including a real mobile robot in a smart home environment and a user.

Saffiotti, Alessandro

Abstract [en]

Under what conditions should a cognitive robot act? How do we define “opportunities” for robot action? How can we characterize their properties? In this po-sition paper, we offer an initial apparatus to formalize opportunities and to frame this discussion.

Abstract [en]

Despite the inter-relationship between physical, cognitive and social factors for older people, the frequency of physical activity typically decreases with age. In this paper, we focus on two specific issues related to physical activity and older people - overcoming the knowledgebarrier and promoting social motivation. We develop a tablet-based prototype called Agile Life that provides ‘Physical Activity Information Chunks’ (PAICs) and also promotes awareness of friends’ activities and opportunities to join in. The results of a user study, including a think-aloud walkthrough and an adapted technology probe, suggest that the social engagement with friends is a strong motivator but that the content of information chunks need to be carefully tailored to the participant. We provide suggestions for further developing an activity application for this age group.